The present invention relates generally to methods of predictive medicine and more specifically to methods of determining expression profiles of an individual.
Every living organism utilizes genetic information in the form of discrete nucleotide sequences, called genes, to convey information for the proper development and function of the organism. Even simple organisms, such as bacteria, contain thousands of genes, and the number is many fold greater in complex organisms such as humans. Understanding the complexities of the development and functioning of living organisms requires knowledge of these genes.
For many years, scientists have searched for and identified a number of genes important in the development and function of living organisms. What was once a difficult and time consuming process has greatly accelerated in recent years due to advances in technology and directed projects aimed at identifying essentially all genetic information of an organism. The first draft of the human genome is now available, and more than 30 organisms have now had their entire genomes sequenced. The determination of the genome of additional organisms is currently being pursued.
One of the most ambitious of these genomic projects has been the Human Genome Project, with the goal of sequencing the entire human genome. The vast amount of genetic information available from the Human Genome Project provides a rich resource of potential targets for drug discovery as well as new diagnostic tools for medicine.
Although the determination of essentially all genes expressed in an organism is a rich resource of information, there remains the daunting task of applying this knowledge in a manner that is useful for practical medical applications. Perhaps 80,000 genes are expressed in human, and the analysis of such a large number of genes is complex. Moreover, in addition to the large number of genes, another layer of complexity arises from alternative splicing of mRNA and various modifications of proteins encoded by the genes. Furthermore, these gene expression patterns are expected to change when a individual has a disease. Information on gene expression patterns thus provides a basis for efficient and accurate diagnostic methods based on changes in gene expression in various diseases. The exploitation of genomics and proteomics information thus requires methods that can account for the large number of genes and complexity of gene expression patterns useful for medical applications. Fully exploiting genomics and proteomics information for medical applications requires methods that can accurately and efficiently monitor complex changes in gene expression patterns both at the mRNA and protein levels.
Thus, there exists a need for methods to efficiently diagnose a disease based on gene expression patterns in an individual. The present invention satisfies this need and provides related advantages as well.